Modeling the population dynamics of herring in the Prince William Sound, Alaska

Abstract

The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska crashed in 1992-93 and has yet to recover, affecting food web dynamics in the Sound and impacting Alaskan communities. To help researchers design and implement the most effective monitoring, management, and recovery programs, a Bayesian assessment of Prince William Sound herring was developed and conducted by reformulating the current model used by Alaska Department of Fish and Game to manage this population. The pre-season spawning biomass of herring age-3 and older in 2013 was estimated to be between 12,150 and 31,740 mt (95% credibility interval) with a median of 19,410 mt. There was a 54% probability that biomass in 2013 was below the management limit used to regulate fisheries in Prince William Sound. This work could be the basis for managing herring in Prince William Sound in combination with a decision rule that explicitly considers uncertainty. A Monte-Carlo simulation study, using the Bayesian Prince William Sound herring assessment model, was conducted to determine which historical sampling programs have provided the most valuable data for forecasting biomass. Tradeoffs were explored between the cost of running each survey and the improvement in model performance due to the inclusion of that survey’s data. The disease survey (which is relatively cheap and collects an index of additional mortality due to disease) and the diver survey (which is relatively expensive and collects an absolute index of abundance) were found to be the most valuable sampling programs. For $10,000 a year the disease survey reduces bias and imprecision in the forecast by 34% on average, increases model reliability by 22%, and decreases by 31% the probability of a false management conclusion when regulating the fishery. For $350,000 a year the diver survey reduces bias and imprecision in the forecast by 12% on average, increases model reliability by 6%, and decreases the probability of a false management conclusion by 23%. This work is directly useful to Pacific herring assessment scientists and provides critical information about how to prioritize research and monitoring efforts to better understand the past and future ecology of Prince William Sound herring.